Open Access
Int. J. Simul. Multisci. Des. Optim.
Volume 5, 2014
Article Number A15
Number of page(s) 6
Published online 10 February 2014
  1. Branke J, Deb K, Miettinen K, Słowinski R. 2008. Multi-objective optimization. Springer Berlin/Heidelberg, New York.
  2. Coello C, Dehuri S, Ghosh S. 2009. Swarm intelligence for multi-objective problems in data mining. Springer, Berlin/Heidelberg, New York. [CrossRef]
  3. Knowles J, Nakayama H. 2008. Meta-modeling in multiobjective optimization. Springer, Berlin/Heidelberg, New York.
  4. Kshetrapalapuram KK, Kirley M. 2005. Mining classification rules using evolutionary multi-objective algorithms. Knowledge-based intelligent, information and engineering systems, 3683, Springer, Berlin/Heidelberg, New York.
  5. Freitas AA. 1998. On objective measures of rule surprisingness, in Principles of data mining and knowledge discovery, Springer Berlin, Heidelberg, pp. 1–9. [CrossRef]
  6. Rowland J. 2003. Generalisation and model selection in supervised learning with evolutionary computation, in Applications of Evolutionary Computing, Springer Berlin, Heidelberg, pp. 119–130.
  7. Obayashi S. 2005. Evolutionary multiobjective optimization and visualization, in New Developments in Computational Fluid Dynamics, Springer Berlin, Heidelberg, pp. 175–185.
  8. Witkowski K, Tushar M. 2009. Decision making in multiobjective optimization for industrial application-Data mining and visualization of Pareto, In Proceedings of 7th European LS-DYNA Conference, USA, 416–423.
  9. Deb K. 2007. Current trends in evolutionary multi-objective optimization. Int. J. Simul. Multidisci. Des. Optim., 2, 1–8. [CrossRef] [EDP Sciences]
  10. Bruyneel M, Colson B, Jetteur P, Raick C, Remouchamps A, Grihon S. 2008. Recent progress in the optimal design of composite structures: industrial solution procedures on case studies. Int. J. Simul. Multidisci. Des. Optim., 2, 283–288. [CrossRef] [EDP Sciences]
  11. Bedingfield SE, Smith KA. 2003. Evolutionary Rule Generation classification and its Application to multi-class data. In Computational Science – ICCS 2003, Springer Berlin Heidelberg, 868–876. [CrossRef]
  12. Mosavi A. 2010. Multiple criteria decision-making pre-processing using data mining tools. IJCSI, International Journal of Computer Science Issues, 7, 26–34.
  13. Arularasan V. 2008. Modeling and simulation of a parallel plate heat sink using computational fluid dynamics. Int. J. Adv. Manuf. Technol., 5, 172–183.
  14. Esmaeili M, Mosavi A. 2010. Variable reduction for multi-objective optimization using data mining techniques; application to aerospace structures. Proceedings of the 2nd International IEEE Conference on Computer Engineering and Technology, 5, 333–337.
  15. Olcer AI. 2007. A hybrid approach for multi-objective combinatorial optimization problems in ship design and shipping. Computers & Operations Research, 35, 2760–2775. [CrossRef]
  16. Toussaint L, Lebaal N, Schlegel D, Gomes S. 2010. Automatic optimization of air conduct design using experimental data and numerical results. Int. J. Simul. Multidisci. Des. Optim., 4, 77–83. [CrossRef] [EDP Sciences]
  17. Bo Y, Any X. 2008. Aerodynamic optimization of 3D wing based on iSIGHT. Appl. Math. Mech. -Engl. Ed., 5, 603–610.
  18. Bluntzer J-B, Gomes S, Bassir DH, Varret A, Sagot JC. 2008. Direct multi-objective optimization of parametric geometrical models stored in PLM systems to improve functional product design. Int. J. Simul. Multidisci. Des. Optim., 2, 83–90. [CrossRef] [EDP Sciences]
  19. Vik P, Luís D, Guilherme P, Oliveira J. 2010. Automatic generation of computer models through the integration of production systems design software tools. Int. J. Simul. Multidisci. Des. Optim., 4, 141–148. [CrossRef] [EDP Sciences]
  20. Mosavi A. 2009. Hydrodynamic design and optimization: application to design a general case for extra equipments on the submarine’s hull. Proceedings of the International IEEE Conference on Computer Technology and Development, 2, 139–143.
  21. Filomeno R, Coelho C, Breitkopf P, Knopf-Lenoir C. 2008. Model reduction for multidisciplinary optimization-application to a 2D wing. Struct. Multidisc. Optim., 7, 29–48. [CrossRef]
  22. Albers A, Leon-Rovira N. 2009. Development of an engine crankshaft in a framework of computer-aided innovation. Computers in Industry, 60, 604–612. [CrossRef]

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